You signed in with another tab or window. Reload to refresh your session.You signed out in another tab or window. Reload to refresh your session.You switched accounts on another tab or window. Reload to refresh your session.Dismiss alert
System integrated with YOLOv4 and Deep SORT for real-time crowd monitoring, then perform crowd analysis. The system is able to monitor for abnormal crowd activity, social distance violation and restricted entry. The other part of the system can then process crowd movement data into optical flow, heatmap and energy graph.
AI-powered multi-camera surveillance with posture classification, fall/inactivity detection, heatmaps, and real-time alerts. Built using OpenCV, MediaPipe, Streamlit & Flask.
Crowd monitoring and management using real-time data from IP camera and Laptop camera footage which aims to provide users with insights into the crowd density at various locations espicially at local market places , shops ,malls. This helps users make informed decisions about visiting places based on the level of crowdiness.
Face Recognition from Crowd by using yolov7 .Extracting the faces from a video/image/live source, which is then passed to the custom facenet network in order to recognize the peoples
Full-stack web application for the visualization of road attributes and route planning in Amsterdam using area avoidance, focusing on the needs of the elderly and vulnerable people.
The Smart Queue Monitor is a real-time computer vision system that uses YOLOv8n and DeepSort to detect and track people in queue and service areas. It provides live analytics including queue length, waiting times, average service duration, and status alerts. With dynamic ROI adjustment, smooth tracking, and privacy features like face blurring
Local-first AI platform for real-time airport operations monitoring, combining edge computer vision, deterministic risk assessment, and an on-premise LLM.
SurakshaSetu is an AI-powered crowd safety and smart event management platform built for festivals, religious gatherings, and large public events. It provides real-time crowd density monitoring, live heatmaps, congestion alerts, intelligent route guidance, emergency response support, and analytics to help organizers and authorities prevent stampede
Real-time people counting and crowd monitoring using YOLO11 | AI-powered bidirectional tracking | Perfect for schools, retail, exhibitions | Raspberry Pi ready
The Doorway Traffic Counter project is a real-time monitoring system designed to track and analyze foot traffic through an entryway. It provides essential features like traffic counting, data analysis, and customizable notifications, with potential for future enhancements to improve user experience and functionality.